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Record W2943310035 · doi:10.9734/sajsse/2019/v3i330105

IFRS Adoption and Bank Performance in Nigeria and Canada Banks

2019· article· en· W2943310035 on OpenAlexaboutno aff
Ayodeji Temitope Ajibade, Terdoo Phoebe Nyikyaa, Nguavese Miriam Nyikyaa

Bibliographic record

VenueSouth Asian Journal of Social Studies and Economics · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsInternational Financial Reporting StandardsAccountingBusinessAuditOrder (exchange)EarningsFinance

Abstract

fetched live from OpenAlex

The aim of this study is to examine the effect of adopted International Financial Reporting Standards (IFRS) adoption on the financial performance of banks in Nigeria and Canada. The study made use of cross sectional data obtained for a period of 10 years from 2006 to 2017, while the regression analysis was used to examine the impact of IFRS adoption on the earnings of 5 banks in Nigeria and Canada. The study found a significant and positive relationship between IFRS adoption and the banks in Nigeria and Canada. The study concludes that IFRS adoption has improved the decision making capability of the various stakeholders, thus, increasing investor confidence. The study suggests that, in order to safeguard the suitable adoption of IFRS in Nigeria and Canada, competent Accountants and Auditors in IFRS are required in large number and that the Institute of Chartered Accountants of Nigeria and Canada must intensify it efforts in organizing IFRS based training programs for its members and other parties connected with corporate reporting.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.243
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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